Tag Archives: RWE

MDIC Annual Public Forum

APF 2024: Shaping the Future of Real-World Evidence and AI in Healthcare

By Erica Freeze
MDIC Annual Public Forum

The MDIC Annual Public Forum 2024 kicked off this week with experts from the National Evaluation System for health Technology (NEST), the Centers for Medicare and Medicaid Services (CMS), and the FDA. Topics included the future of real-world evidence (RWE) and the integration of AI into the healthcare ecosystem and how can we leverage emerging technologies to bring innovative and safer solutions to patients.

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Bridging Regulatory & Reimbursement

Everybody is looking for Evidence — Bridging Regulatory & Reimbursement: Strategies for Success

By Christy Sheehy, PhD, Jenny Levinson
Bridging Regulatory & Reimbursement

As medical technology products and services move through the development pipeline, they face the challenge of both showing safety and efficacy for regulatory approval and articulating the value of the diagnostic, treatment or monitoring technology to obtain reimbursement from payers. A 2024 MedExec Women Conference panel highlighted strategies to bridge the evidence needs for regulatory approval and reimbursement to more efficiently bring products to market.

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Post-market surveillance

Reliable Active Surveillance: RWE for MedTech

By Amelia Hufford, PhD, Phillip Stoltzfus
Post-market surveillance

As regulatory bodies increasingly recognize the richness and value of RWE, particularly in informing the benefit-risk profile of devices from real-world environments, MedTech companies are turning to advanced analytical tools to navigate this new landscape efficiently.

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Harsha Rajasimha, Ph.D.

AI and the Lack of Diversity in Data: Implications and the Path Forward for Rare Disease Research

By MedTech Intelligence Staff
Harsha Rajasimha, Ph.D.

Genomics data scientist Harsha Rajasimha, Ph.D., Founder and Executive Chairman of IndoUSrare, highlights the risks of developing AI/ML algorithms based on biased data, as well as efforts underway to improve global collaboration on the collection and sharing of health data that may help us realize the potential of AI in diagnoses and treatment of rare diseases.

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